As biopharmaceutical companies bring new products to market, they generally focus on clinical development, regulatory submissions,
and preparation of the target market. Equally as critical is developing the product's commercial supply network. Thoughtful
planning and design of the supply chain during product development significantly impacts not only the efficiency of commercial
supply, but also the flexibility required to accommodate lifecycle changes. Ultimately, the right supply chain can help ensure
the availability of critical and life-saving products to patients who need them. Conversely, an ill-planned supply chain can
increase operating costs, restrict a company's flexibility, and constrain the flow of product to patients.
A supply chain allows the movement of materials, money, and related information from the suppliers of key materials and components
to the end customers or patients. During the years leading up to a product launch, basic strategies and best practices can
be applied to plan, design, and build a product's supply infrastructure. These steps should be followed each time a supply
chain is established, whether it is a company's first or tenth commercial product launch.
START EARLY WITH STRATEGIES
Developing a strategy is the first and most important step in creating a new supply chain. The strategy should identify:
- the general structure of the product's supply chain
- which capabilities will be bought or built internally
- which elements overlap with other products, either approved or in the pipeline.
The supply chain strategy sets the tone for launch-related activities throughout the organization, and helps to shape planning
for other functions, including QA, commercial operations, and finance and development.
ASSUMPTIONS ARE KEY
Early planning is an important insurance policy and helps define which activities are necessary to develop the infrastructure,
and when they need to be completed.
Planning for a commercial supply chain build-out should begin roughly 24 to 30 months before the anticipated commercial launch.
This may vary depending on the duration of clinical trials, and the complexity of technology transfer.
Managers in many life sciences companies hesitate to establish a plan early in the development stage because of all the unknowns
surrounding key supply chain variables, such as demand patterns, manufacturing yields, and stability ranges. It is helpful
to document a preliminary set of working assumptions to initiate planning and limit the degrees of uncertainty. This helps
to clarify intent, communicate consistently across the organization, and allow departments to conduct their own functional
In many emerging companies, supply chain expertise does not exist early on, and there is a long delay in filling key internal
roles. Planning can become fragmented, with various individuals and functions developing the supply chain. Sometimes, planning
is well-defined for certain parts of the supply chain, like manufacturing, but not for others, like packaging and distribution.
Planners should focus on relevance over precision; they should review documents regularly, changing them as new information
becomes available throughout development and launch preparation.
DESIGNING A SUPPLY CHAIN
Developing a detailed design for the commercial supply chain should be done early and include an in-depth description of the
numbers and types of organizations involved, required business processes, definitions of internal and external roles, required
information flow, underlying applications, and existing constraints.
Supply chain design requires considering the product itself (storage and handling requirements), requirements for market or
therapeutic area (complementary components, packaging, channels), and regulatory strategy. Flexibility and resilience should
be built into the supply network to handle fluctuations and unexpected events. Companies should develop preliminary performance
models to examine the behavior of the prospective supply chain along key metrics. This will provide a baseline expectation
of performance that can be used for budgeting and planning, and for developing contingency plans. Such models may be spreadsheet
based, but companies can also use more sophisticated modeling and optimization tools.